Antenna Season Report Notebook¶

Josh Dillon, Last Revised January 2022

This notebook examines an individual antenna's performance over a whole season. This notebook parses information from each nightly rtp_summarynotebook (as saved to .csvs) and builds a table describing antenna performance. It also reproduces per-antenna plots from each auto_metrics notebook pertinent to the specific antenna.

In [1]:
import os
from IPython.display import display, HTML
display(HTML("<style>.container { width:100% !important; }</style>"))
In [2]:
# If you want to run this notebook locally, copy the output of the next cell into the next line of this cell.
# antenna = "004"
# csv_folder = '/lustre/aoc/projects/hera/H5C/H5C_Notebooks/_rtp_summary_'
# auto_metrics_folder = '/lustre/aoc/projects/hera/H5C/H5C_Notebooks/auto_metrics_inspect'
# os.environ["ANTENNA"] = antenna
# os.environ["CSV_FOLDER"] = csv_folder
# os.environ["AUTO_METRICS_FOLDER"] = auto_metrics_folder
In [3]:
# Use environment variables to figure out path to the csvs and auto_metrics
antenna = str(int(os.environ["ANTENNA"]))
csv_folder = os.environ["CSV_FOLDER"]
auto_metrics_folder = os.environ["AUTO_METRICS_FOLDER"]
print(f'antenna = "{antenna}"')
print(f'csv_folder = "{csv_folder}"')
print(f'auto_metrics_folder = "{auto_metrics_folder}"')

antenna = "228"
csv_folder = "/home/obs/src/H6C_Notebooks/_rtp_summary_"
auto_metrics_folder = "/home/obs/src/H6C_Notebooks/auto_metrics_inspect"
In [4]:
display(HTML(f'<h1 style=font-size:50px><u>Antenna {antenna} Report</u><p></p></h1>'))

Antenna 228 Report

In [5]:
import numpy as np
import pandas as pd
pd.set_option('display.max_rows', 1000)
import glob
import re
from hera_notebook_templates.utils import status_colors, Antenna
In [6]:
# load csvs and auto_metrics htmls in reverse chronological order
csvs = sorted(glob.glob(os.path.join(csv_folder, 'rtp_summary_table*.csv')))[::-1]
print(f'Found {len(csvs)} csvs in {csv_folder}')
auto_metric_htmls = sorted(glob.glob(auto_metrics_folder + '/auto_metrics_inspect_*.html'))[::-1]
print(f'Found {len(auto_metric_htmls)} auto_metrics notebooks in {auto_metrics_folder}')

Found 22 csvs in /home/obs/src/H6C_Notebooks/_rtp_summary_
Found 22 auto_metrics notebooks in /home/obs/src/H6C_Notebooks/auto_metrics_inspect
In [7]:
# Per-season options
mean_round_modz_cut = 4
dead_cut = 0.4
crossed_cut = 0.0

def jd_to_summary_url(jd):
    return f'https://htmlpreview.github.io/?https://github.com/HERA-Team/H6C_Notebooks/blob/main/_rtp_summary_/rtp_summary_{jd}.html'

def jd_to_auto_metrics_url(jd):
    return f'https://htmlpreview.github.io/?https://github.com/HERA-Team/H6C_Notebooks/blob/main/auto_metrics_inspect/auto_metrics_inspect_{jd}.html'

Load relevant info from summary CSVs¶

In [8]:
this_antenna = None
jds = []

# parse information about antennas and nodes
for csv in csvs:
    df = pd.read_csv(csv)
    for n in range(len(df)):
        # Add this day to the antenna
        row = df.loc[n]
        if isinstance(row['Ant'], str) and '<a href' in row['Ant']:
            antnum = int(row['Ant'].split('</a>')[0].split('>')[-1]) # it's a link, extract antnum
        else:
            antnum = int(row['Ant'])
        if antnum != int(antenna):
            continue
        
        if np.issubdtype(type(row['Node']), np.integer):
            row['Node'] = str(row['Node'])
        if type(row['Node']) == str and row['Node'].isnumeric():
            row['Node'] = 'N' + ('0' if len(row['Node']) == 1 else '') + row['Node']
            
        if this_antenna is None:
            this_antenna = Antenna(row['Ant'], row['Node'])
        jd = [int(s) for s in re.split('_|\.', csv) if s.isdigit()][-1]
        jds.append(jd)
        this_antenna.add_day(jd, row)
        break
In [9]:
# build dataframe
to_show = {'JDs': [f'<a href="{jd_to_summary_url(jd)}" target="_blank">{jd}</a>' for jd in jds]}
to_show['A Priori Status'] = [this_antenna.statuses[jd] for jd in jds]

df = pd.DataFrame(to_show)

# create bar chart columns for flagging percentages:
bar_cols = {}
bar_cols['Auto Metrics Flags'] = [this_antenna.auto_flags[jd] for jd in jds]
bar_cols[f'Dead Fraction in Ant Metrics (Jee)'] = [this_antenna.dead_flags_Jee[jd] for jd in jds]
bar_cols[f'Dead Fraction in Ant Metrics (Jnn)'] = [this_antenna.dead_flags_Jnn[jd] for jd in jds]
bar_cols['Crossed Fraction in Ant Metrics'] = [this_antenna.crossed_flags[jd] for jd in jds]
bar_cols['Flag Fraction Before Redcal'] = [this_antenna.flags_before_redcal[jd] for jd in jds]
bar_cols['Flagged By Redcal chi^2 Fraction'] = [this_antenna.redcal_flags[jd] for jd in jds]
for col in bar_cols:
    df[col] = bar_cols[col]

z_score_cols = {}
z_score_cols['ee Shape Modified Z-Score'] = [this_antenna.ee_shape_zs[jd] for jd in jds]
z_score_cols['nn Shape Modified Z-Score'] = [this_antenna.nn_shape_zs[jd] for jd in jds]
z_score_cols['ee Power Modified Z-Score'] = [this_antenna.ee_power_zs[jd] for jd in jds]
z_score_cols['nn Power Modified Z-Score'] = [this_antenna.nn_power_zs[jd] for jd in jds]
z_score_cols['ee Temporal Variability Modified Z-Score'] = [this_antenna.ee_temp_var_zs[jd] for jd in jds]
z_score_cols['nn Temporal Variability Modified Z-Score'] = [this_antenna.nn_temp_var_zs[jd] for jd in jds]
z_score_cols['ee Temporal Discontinuties Modified Z-Score'] = [this_antenna.ee_temp_discon_zs[jd] for jd in jds]
z_score_cols['nn Temporal Discontinuties Modified Z-Score'] = [this_antenna.nn_temp_discon_zs[jd] for jd in jds]
for col in z_score_cols:
    df[col] = z_score_cols[col]

ant_metrics_cols = {}
ant_metrics_cols['Average Dead Ant Metric (Jee)'] = [this_antenna.Jee_dead_metrics[jd] for jd in jds]
ant_metrics_cols['Average Dead Ant Metric (Jnn)'] = [this_antenna.Jnn_dead_metrics[jd] for jd in jds]
ant_metrics_cols['Average Crossed Ant Metric'] = [this_antenna.crossed_metrics[jd] for jd in jds]
for col in ant_metrics_cols:
    df[col] = ant_metrics_cols[col]

redcal_cols = {}
redcal_cols['Median chi^2 Per Antenna (Jee)'] = [this_antenna.Jee_chisqs[jd] for jd in jds]
redcal_cols['Median chi^2 Per Antenna (Jnn)'] = [this_antenna.Jnn_chisqs[jd] for jd in jds]   
for col in redcal_cols:
    df[col] = redcal_cols[col]

# style dataframe
table = df.style.hide_index()\
          .applymap(lambda val: f'background-color: {status_colors[val]}' if val in status_colors else '', subset=['A Priori Status']) \
          .background_gradient(cmap='viridis', vmax=mean_round_modz_cut * 3, vmin=0, axis=None, subset=list(z_score_cols.keys())) \
          .background_gradient(cmap='bwr_r', vmin=dead_cut-.25, vmax=dead_cut+.25, axis=0, subset=list([col for col in ant_metrics_cols if 'dead' in col.lower()])) \
          .background_gradient(cmap='bwr_r', vmin=crossed_cut-.25, vmax=crossed_cut+.25, axis=0, subset=list([col for col in ant_metrics_cols if 'crossed' in col.lower()])) \
          .background_gradient(cmap='plasma', vmax=4, vmin=1, axis=None, subset=list(redcal_cols.keys())) \
          .applymap(lambda val: 'font-weight: bold' if val < dead_cut else '', subset=list([col for col in ant_metrics_cols if 'dead' in col.lower()])) \
          .applymap(lambda val: 'font-weight: bold' if val < crossed_cut else '', subset=list([col for col in ant_metrics_cols if 'crossed' in col.lower()])) \
          .applymap(lambda val: 'font-weight: bold' if val > mean_round_modz_cut else '', subset=list(z_score_cols.keys())) \
          .applymap(lambda val: 'color: red' if val > mean_round_modz_cut else '', subset=list(z_score_cols.keys())) \
          .bar(subset=list(bar_cols.keys()), vmin=0, vmax=1) \
          .format({col: '{:,.4f}'.format for col in z_score_cols}) \
          .format({col: '{:,.4f}'.format for col in ant_metrics_cols}) \
          .format('{:,.2%}', na_rep='-', subset=list(bar_cols.keys())) \
          .set_table_styles([dict(selector="th",props=[('max-width', f'70pt')])])

Table 1: Per-Night RTP Summary Info For This Atenna¶

This table reproduces each night's row for this antenna from the RTP Summary notebooks. For more info on the columns, see those notebooks, linked in the JD column.

In [10]:
display(HTML(f'<h2>Antenna {antenna}, Node {this_antenna.node}:</h2>'))
HTML(table.render(render_links=True, escape=False))

Antenna 228, Node N20:

Out[10]:
JDs A Priori Status Auto Metrics Flags Dead Fraction in Ant Metrics (Jee) Dead Fraction in Ant Metrics (Jnn) Crossed Fraction in Ant Metrics Flag Fraction Before Redcal Flagged By Redcal chi^2 Fraction ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score Average Dead Ant Metric (Jee) Average Dead Ant Metric (Jnn) Average Crossed Ant Metric Median chi^2 Per Antenna (Jee) Median chi^2 Per Antenna (Jnn)
2459998 RF_maintenance 0.00% 0.00% 0.00% 0.00% - - 0.518040 0.202045 0.765822 -1.223706 -0.191643 -0.978051 0.824733 1.895592 0.5685 0.5736 0.3692 nan nan
2459997 RF_maintenance 0.00% 0.00% 0.00% 0.00% - - 0.761710 0.519842 1.063019 -1.201315 0.549825 -1.109296 0.894726 1.441650 0.5803 0.5882 0.3678 nan nan
2459996 RF_maintenance 0.00% 0.00% 0.00% 0.00% - - 1.221938 0.760895 0.943929 -1.345856 0.521118 -1.008016 3.321271 1.217071 0.5868 0.5936 0.3787 nan nan
2459995 RF_maintenance 0.00% 0.00% 0.00% 0.00% - - 0.960210 -0.362504 1.015914 -1.490809 0.343041 -0.956320 0.284369 0.548331 0.5864 0.5931 0.3738 nan nan
2459994 RF_maintenance 0.00% 0.00% 0.00% 0.00% - - 0.941922 -0.092650 0.997480 -1.368646 0.236689 -0.791726 -0.197156 0.904074 0.5807 0.5838 0.3695 nan nan
2459993 RF_maintenance 0.00% 0.00% 0.00% 0.00% - - 1.240999 -0.233126 1.239631 -1.265593 1.074380 -1.050783 -0.303305 0.460101 0.5724 0.5858 0.3783 nan nan
2459991 RF_maintenance 0.00% 0.00% 0.00% 0.00% - - 1.046935 -0.089279 1.181137 -1.282900 0.712887 -1.052655 0.087819 1.028085 0.5817 0.5761 0.3790 nan nan
2459990 RF_maintenance 0.00% 0.00% 0.00% 0.00% - - 0.908949 -0.040236 1.193957 -1.222273 0.700799 -1.043551 -0.399680 0.627239 0.5805 0.5777 0.3743 nan nan
2459989 RF_maintenance 0.00% 0.00% 0.00% 0.00% - - 0.813039 0.009187 1.286518 -1.101750 0.607855 -1.148926 -0.274287 0.707586 0.5785 0.5793 0.3764 nan nan
2459988 RF_maintenance 0.00% 0.00% 0.00% 0.00% - - 0.863848 -0.126968 1.224708 -1.263560 0.936495 -1.101168 -0.227214 0.586144 0.5789 0.5821 0.3714 nan nan
2459987 RF_maintenance 0.00% 0.00% 0.00% 0.00% - - 0.629655 -0.280841 1.073643 -1.377693 0.122817 -0.923791 -0.207019 1.014063 0.5862 0.5893 0.3664 nan nan
2459986 RF_maintenance 0.00% 0.00% 0.00% 0.00% - - 1.084300 -0.171169 1.207282 -1.323719 0.527198 -1.371386 0.513099 -0.880466 0.6118 0.6223 0.3245 nan nan
2459985 RF_maintenance 0.00% 0.00% 0.00% 0.00% - - 0.820036 -0.286390 0.984379 -1.405959 0.215859 -1.145110 1.178076 1.405305 0.5880 0.5914 0.3750 nan nan
2459984 RF_maintenance 0.00% 0.00% 0.00% 0.00% - - 0.679849 -0.468267 1.072851 -1.345977 0.382808 -1.667010 0.191038 -0.629326 0.6000 0.6087 0.3564 nan nan
2459983 RF_maintenance 0.00% 0.00% 0.00% 0.00% - - 0.361680 -0.169035 1.113704 -1.187572 0.031202 -0.698306 -0.571277 -0.447189 0.6081 0.6197 0.3315 nan nan
2459982 RF_maintenance 0.00% 0.00% 0.00% 0.00% - - -0.871237 -0.186130 0.490755 -1.125801 -1.227542 -0.885247 -0.746177 -0.978133 0.6775 0.6749 0.2862 nan nan
2459981 RF_maintenance 100.00% 0.00% 0.00% 0.00% - - 6.977158 18.393779 -0.860536 -0.005022 1.604616 6.316070 50.872663 46.430795 0.5241 0.4948 0.3144 nan nan
2459980 RF_maintenance 100.00% 0.00% 0.00% 0.00% - - 6.674144 18.626255 -0.874283 -0.465505 1.505530 3.104370 5.051734 3.616699 0.5878 0.5557 0.2507 nan nan
2459979 RF_maintenance 100.00% 0.00% 0.00% 0.00% - - 7.281839 19.680941 -0.958817 -0.434204 1.227142 2.042108 44.493005 12.527510 0.5179 0.4902 0.3113 nan nan
2459978 RF_maintenance 100.00% 0.00% 0.00% 0.00% - - 5.986215 20.276446 -1.014809 -0.353662 0.404486 3.400990 14.962790 27.329670 0.5276 0.4921 0.3200 nan nan
2459977 RF_maintenance 100.00% 0.00% 0.00% 0.00% - - 9.795298 21.345415 -0.684666 -0.654795 5.338093 3.900429 114.896610 26.876407 0.4586 0.4257 0.2485 nan nan
2459976 RF_maintenance 100.00% 0.00% 0.00% 0.00% - - 4.818371 21.711999 -0.865145 -0.565234 0.865720 3.259141 24.964248 9.032601 0.5349 0.4883 0.3048 nan nan

Load antenna metric spectra and waterfalls from auto_metrics notebooks.¶

In [11]:
htmls_to_display = []
for am_html in auto_metric_htmls:
    html_to_display = ''
    # read html into a list of lines
    with open(am_html) as f:
        lines = f.readlines()
    
    # find section with this antenna's metric plots and add to html_to_display
    jd = [int(s) for s in re.split('_|\.', am_html) if s.isdigit()][-1]
    try:
        section_start_line = lines.index(f'<h2>Antenna {antenna}: {jd}</h2>\n')
    except ValueError:
        continue
    html_to_display += lines[section_start_line].replace(str(jd), f'<a href="{jd_to_auto_metrics_url(jd)}" target="_blank">{jd}</a>')
    for line in lines[section_start_line + 1:]:
        html_to_display += line
        if '<hr' in line:
            htmls_to_display.append(html_to_display)
            break

Figure 1: Antenna autocorrelation metric spectra and waterfalls.¶

These figures are reproduced from auto_metrics notebooks. For more info on the specific plots and metrics, see those notebooks (linked at the JD). The most recent 100 days (at most) are shown.

In [12]:
for i, html_to_display in enumerate(htmls_to_display):
    if i == 100:
        break
    display(HTML(html_to_display))

Antenna 228: 2459998

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
228 N20 RF_maintenance nn Temporal Discontinuties 1.895592 0.518040 0.202045 0.765822 -1.223706 -0.191643 -0.978051 0.824733 1.895592

Antenna 228: 2459997

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
228 N20 RF_maintenance nn Temporal Discontinuties 1.441650 0.761710 0.519842 1.063019 -1.201315 0.549825 -1.109296 0.894726 1.441650

Antenna 228: 2459996

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
228 N20 RF_maintenance ee Temporal Discontinuties 3.321271 1.221938 0.760895 0.943929 -1.345856 0.521118 -1.008016 3.321271 1.217071

Antenna 228: 2459995

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
228 N20 RF_maintenance ee Power 1.015914 0.960210 -0.362504 1.015914 -1.490809 0.343041 -0.956320 0.284369 0.548331

Antenna 228: 2459994

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
228 N20 RF_maintenance ee Power 0.997480 0.941922 -0.092650 0.997480 -1.368646 0.236689 -0.791726 -0.197156 0.904074

Antenna 228: 2459993

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
228 N20 RF_maintenance ee Shape 1.240999 1.240999 -0.233126 1.239631 -1.265593 1.074380 -1.050783 -0.303305 0.460101

Antenna 228: 2459991

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
228 N20 RF_maintenance ee Power 1.181137 1.046935 -0.089279 1.181137 -1.282900 0.712887 -1.052655 0.087819 1.028085

Antenna 228: 2459990

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
228 N20 RF_maintenance ee Power 1.193957 -0.040236 0.908949 -1.222273 1.193957 -1.043551 0.700799 0.627239 -0.399680

Antenna 228: 2459989

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
228 N20 RF_maintenance ee Power 1.286518 0.009187 0.813039 -1.101750 1.286518 -1.148926 0.607855 0.707586 -0.274287

Antenna 228: 2459988

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
228 N20 RF_maintenance ee Power 1.224708 -0.126968 0.863848 -1.263560 1.224708 -1.101168 0.936495 0.586144 -0.227214

Antenna 228: 2459987

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
228 N20 RF_maintenance ee Power 1.073643 0.629655 -0.280841 1.073643 -1.377693 0.122817 -0.923791 -0.207019 1.014063

Antenna 228: 2459986

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
228 N20 RF_maintenance ee Power 1.207282 -0.171169 1.084300 -1.323719 1.207282 -1.371386 0.527198 -0.880466 0.513099

Antenna 228: 2459985

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
228 N20 RF_maintenance nn Temporal Discontinuties 1.405305 -0.286390 0.820036 -1.405959 0.984379 -1.145110 0.215859 1.405305 1.178076

Antenna 228: 2459984

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
228 N20 RF_maintenance ee Power 1.072851 0.679849 -0.468267 1.072851 -1.345977 0.382808 -1.667010 0.191038 -0.629326

Antenna 228: 2459983

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
228 N20 RF_maintenance ee Power 1.113704 0.361680 -0.169035 1.113704 -1.187572 0.031202 -0.698306 -0.571277 -0.447189

Antenna 228: 2459982

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
228 N20 RF_maintenance ee Power 0.490755 -0.871237 -0.186130 0.490755 -1.125801 -1.227542 -0.885247 -0.746177 -0.978133

Antenna 228: 2459981

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
228 N20 RF_maintenance ee Temporal Discontinuties 50.872663 18.393779 6.977158 -0.005022 -0.860536 6.316070 1.604616 46.430795 50.872663

Antenna 228: 2459980

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
228 N20 RF_maintenance nn Shape 18.626255 18.626255 6.674144 -0.465505 -0.874283 3.104370 1.505530 3.616699 5.051734

Antenna 228: 2459979

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
228 N20 RF_maintenance ee Temporal Discontinuties 44.493005 7.281839 19.680941 -0.958817 -0.434204 1.227142 2.042108 44.493005 12.527510

Antenna 228: 2459978

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
228 N20 RF_maintenance nn Temporal Discontinuties 27.329670 20.276446 5.986215 -0.353662 -1.014809 3.400990 0.404486 27.329670 14.962790

Antenna 228: 2459977

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
228 N20 RF_maintenance ee Temporal Discontinuties 114.896610 9.795298 21.345415 -0.684666 -0.654795 5.338093 3.900429 114.896610 26.876407

Antenna 228: 2459976

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
228 N20 RF_maintenance ee Temporal Discontinuties 24.964248 21.711999 4.818371 -0.565234 -0.865145 3.259141 0.865720 9.032601 24.964248
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